Biomarker is a substance, structure, or process that serves as a quantifiable and measurable indicator of a general biological pattern. In recent years, machine learning technology has emerged in various fields with its unique advantages, and has attracted wide attention and research. With the rapid development of high-throughput sequencing and multi-omics technology, compared with classical statistical methods, machine learning technology can better conduct in-depth analysis and mining of massive omics data, and show great prospects in analyzing the potential relationships of high-dimensional data. The use of machine learning technologies to screen biomarkers has been widely used in precision medicine and clinical research, physiological mechanism research, molecular breeding, ecology and environment and other fields.

  • We have developed MLBiomarker, a biomarker analysis and visualization platform based on machine learning. The platform integrates 14 machine learning technologies for binary/multi-classification data analysis, 11 machine learning technologies for survival analysis, and provides services such as model / biomarker evaluation and KM (Kaplan-Meier) analysis to help users find the most suitable machine learning technology. Then the optimal model and biomarker set were screened. In addition, there are 7 cluster analysis methods for users to choose, and functional enrichment analysis can be performed when the type of feature is gene symbol.
  • Click the button on the left to enter the analysis page.
  • Case files are available in the table below.

Download of Case Files

  Biomarker Identification

Analysis Class Matrix File Group File Reference


Survival Analysis


  Biomarker Evaluation

Analysis Class List of Biomarkers Matrix File Group File
Survival Analysis

  Clustering Analysis

  Matrix File:  

  Functional Research

  List of Gene Symbol: